class_docstr: Class for storing a causal estimand, as a result of the identification step using the ID algorithm.
  The object stores a list of estimators(self._product) whose porduct must be obtained and a list of variables (self._sum) over which the product must be marginalized.
class_docstr_tok: ["Class","for","storing","a","causal","estimand",",","as","a","result","of","the","identification","step","using","the","ID","algorithm",".","The","object","stores","a","list","of","estimators","(","self._product",")","whose","porduct","must","be","obtained","and","a","list","of","variables","(","self._sum",")","over","which","the","product","must","be","marginalized","."]
docstr: Add variables to the list.
  
  :param element: Set of variables to append to the list self._sum.
docstr_tok: ["Add","variables","to","the","list",".",":","param","element",":","Set","of","variables","to","append","to","the","list","self._sum","."]
code: def add_sum(self, element: Set):
      """
      Add variables to the list.
  
      :param element: Set of variables to append to the list self._sum.
      """
      for el in element:
          self._sum.append(el)
  
file_path: dowhy/dowhy/causal_identifier/id_identifier.py
imports: from typing import Dict, List, Optional, Set, Union
  import networkx
  import numpy
  from dowhy.graph import get_adjacency_matrix
  from dowhy.utils.api import parse_state
  from dowhy.utils.graph_operations import find_ancestor, find_c_components, induced_graph
  from dowhy.utils.ordered_set import OrderedSet
label_desc: Use image node_id 3 for calling the IDExpression obj's underlying member method code with example usage: obj.add_sum(element) without return types